Identifying the accumulator: Making the most of bone surface modification data
Autor: | J. Tyler Faith, Jamie Hodgkins, Jessica C. Thompson, Naomi Cleghorn |
---|---|
Rok vydání: | 2017 |
Předmět: |
010506 paleontology
Archeology 060101 anthropology Taphonomy Comparability Experimental data 06 humanities and the arts Biology 01 natural sciences Data science Paleontology Sample size determination Assemblage (archaeology) 0601 history and archaeology Robustness (economics) Zooarchaeology Oldowan 0105 earth and related environmental sciences |
Zdroj: | Journal of Archaeological Science. 85:105-113 |
ISSN: | 0305-4403 |
Popis: | Taphonomic analysis is an essential component of zooarchaeology, but is employed in different ways within different research traditions. Within the Africanist Palaeolithic literature, there is a strong emphasis on quantitative comparison of proportions of different bone surface modifications to one another and to proportions observed on modern experimental collections. This work has been driven by debates about the taphonomic histories of Oldowan sites that document the subsistence strategies of early Homo, but this specific approach can be usefully applied to a range of contexts across many different time periods and geographic locations. One obstacle to the cross-fertilization of this taphonomic tradition with other zooarchaeological work is the restrictive manner in which data are selected from an assemblage for analysis. To ensure comparability between fossil and modern assemblages, analysts typically exclude specimens with evidence for post-depositional modification not modeled in the experimental data. Although this adds interpretive robustness, it can diminish sample size significantly, sometimes to the point of affecting statistical analyses, and results in much time invested in collecting data that ultimately are not used. Here, we describe a new method for maximizing the number of specimens that can be incorporated into analysis, thus resolving the persistent problem of poor sample sizes to make more statistically robust comparisons to actualistic datasets. |
Databáze: | OpenAIRE |
Externí odkaz: |